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Quotes about ... permutation tests


"Statistics is more a way of thinking or reasoning
than a bunch of prescriptions for beating data to elicit answers."
C. R. Rao "Statististics and Truth. Putting Chance to Work", p. 60.
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"Normality is a myth; there never has, and never will be,
a normal distribution.
R. C. Geary (1947). Testing for Normality. Biometrika, 34, 209-242.
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"Statistical thinking will one day be as necessary for efficient citizenship
as the ability to read and write."
In 1923 Jerzy Spława-Neyman introduced a permutation model for the analysis of agricultural field experiments. This early paper used permutation methods to compare and evaluate differences among several crop varieties.
Berry K. J., Johnston J. E., Mielke Jr. P. W. (2014) , p. 21.
In 1933, J. Neyman and E.S. Pearson provided a method for determining the most efficient test of a hypothesis [...] Unfortunately, by this time, theory had outrun practice. These new permutation methods were beyond the capabilities of the mechanical computing devices of the 1930s–1940s.
Good (2005) p. 11.
Five Steps to a Test
1. Analyze the problem—identify the hypothesis, the alternative hypotheses of interest, and the potential risks associated with a decision.
2. Choose a test statistic.
3. Compute the test statistic.
4. Determine the frequency distribution of the test statistic under the hypothesis.
5. Make a decision using this distribution as a guide.
Good P. (2005) p.8.
Permutation tests are often described as the gold standard against which conventional parametric tests are tested and evaluated.
Berry K. J., Johnston J. E., Mielke Jr. P. W. (2014) , p. 1.
Permutation tests are often termed “data-dependent” tests because all the information available for analysis is contained in the observed data set. [...] Thus, permutation tests are distribution-free tests in that the tests do not assume distributional properties of the population.
Mielke P. W., Berry K. J. Jr. (2007) p. 3.
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